Depression and Anxiety Among COVID-19 Patients Admitted to a "Red Zone" Intensive Care Unit: Do the Factors of Self-Awareness of Somatic Health, Anxiety, and Depression Contribute to the Course of Sars-Cov-2 Infection?

BACKGROUND: The prevalence of depressive disorders in the general population increased significantly during the COVID-19 pandemic. The aim of this study is to examine the relationship between history of anxiety and depressive disorders and COVID-19 outcome, hospitalization and severity of anxiety and depression, and whether such relationships are explicable by direct impact of the disease. SUBJECTS AND METHODS: We conducted a questionnaire survey among 98 inpatients in the Department of Infectious Diseases of the Clinics of Samara State Medical University. The self-report questionnaire consisted of 120 items, including socio-demographic characteristics of participants, State-Trait Anxiety Inventory, and the Center for Epidemiologic Studies Depression Scale, with items reflecting subjective feelings about the COVID-19 pandemic. We used one-factor analysis of variance to compare between groups for those indicators that conformed to a normal distribution, and the chi-square test (χ2) or Fisher's exact test to analyze group differences in the distribution of categorical variables was used. RESULTS: The mean (SD) total score on the STAI anxiety scale among hospitalized patients (51 (10.1)) significantly exceeded that of the COMET-G control group (44.9 (11.7) (H=22.8, p<0.001). There was a similar difference in the severity of depression as measured by the CES-D scale (23.4 (12.6) versus 18.0 (11.8), H=15.2 and p<0.001). In contrast to the general population, there were no statistically significant differences in anxiety and depression severity in the matched samples 52 subjects fulfilling the criteria of age, gender, and general perception of health condition. CONCLUSIONS: Anxiety and depression scores among ICU (red zone) inpatients significantly exceeded the scores observed in the COMET-G general population group. Our study did not confirm expected relationship between symptoms of anxiety and depression (based on questionnaire response) and the risk of severe course of COVID-19 (e.g. hospitalization) in matched samples, but proved that the factor of self-awareness of health state may be related to the COVID-19 course severity. Future research would benefit from clinical interview of inpatients and follow-up monitoring of affective disorders to specify whether anxiety and particular type of depression (e.g., anxious) are selectively related to the severity of COVID-19 course and risks of affective disorders persistence after somatic recovery. The accumulation of mental disorders with age, and the bidirectional association of mood disorders and infectious diseases should be considered when assessing the risk factors.

Systematic Review and Meta-Analysis Confirm the Moderate Efficacy of High-Frequency r-TMS in Alzheimer's Disease: Mediating Effects of Anhedonia-Apathy and Add-On Motor-Cognitive Excersizes.

OBJECTIVES: Alzheimer's disease (AD) presents a major global health issue of significant socio-economic impact. Pharmacological treatments for AD have limited efficacy, prompting the exploration of alternative therapies, such as repetitive transcranial magnetic stimulation (rTMS), a promising non-invasive technique to enhance cognitive function in AD patients. Our systematic review and meta-analysis aim to evaluate the efficacy of rTMS in relation to cognitive function in AD patients, identify optimal rTMS stimulation parameters, and understand the underlying neural mechanisms. METHODS: We conducted a comprehensive literature search in PubMed using predefined search terms to identify original research articles investigating the effects of rTMS on cognitive function in AD patients. We selected only randomized controlled trials (RCTs) with sufficient quantitative data for comparing active rTMS to the sham-coil treatment, and then performed a random effects meta-analysis using standardized mean differences (SMDs) to synthesize the effects across studies. RESULTS: The systematic review included 22 studies, among which 14 RCTs met our criteria for meta-analysis. High-frequency rTMS, particularly targeting the dorsolateral prefrontal cortex (DLPFC), evoked significant cognitive improvements in AD patients, with a moderate positive effect size of rTMS on cognitive function (Hedges' g=0.580, 95% CI [0.268, 0.892], p<0.001), albeit with substantial heterogeneity (I²=59%). Funnel plot asymmetry and Egger's test suggested a potential publication bias, but fail-safe N analysis indicated a robust finding. Moreover, anhedonia-apathy symptoms and motor-cognitive exercises mediated the efficacy of tTMS in ameliorating cognitive functioning across several studies. CONCLUSION: rTMS demonstrates moderate efficacy in improving cognitive function in AD-patients, most distinctly with high-frequency rTMS stimulation protocols targeting the DLPFC area. The meta-analysis support rTMS as a viable therapeutic intervention for cognitive enhancement in AD. Future promising research should focus on personalized treatment strategies targeting mediating factors, baseline connectivity patterns, and TMS-induced neuroplasticity in AD.

Risk Assessment Suicidality Scale (RASS)-Based On-Line Calculator Targeting Early Prevention of Suicides in General Population: from COMET-G Study Results Towards Integration of the Screening Tool into Routine Clinical Practice.

BACKGROUND: Suicide is a major global health concern, particularly among young people. This study evaluates an online suicide risk calculator based on the Risk Assessment of Suicidality Scale (RASS), which is designed to enhance accessibility and early detection of suicide risk. METHODS: The study involved 444 participants who completed the RASS via an online calculator. Results were compared with data from the COMET-G study's Russian sample (n=7572). Descriptive statistics, correlation analysis, and two-way ANOVA were used to analyze the data. RESULTS: The mean age of participants was 22.71 years (SD=7.94). The mean total RASS standardized score was 837.7 (SD=297.8). There was a significant negative correlation between age and RASS scores (r=-0.463, p<0.0001). The online calculator sample showed significantly higher RASS scores compared to the COMET-G sample, with 71% of online users scoring above the 90th percentile of the COMET-G sample. CONCLUSION: Our study demonstrated the advantage of the on-line suicidality risk calculator based on the RASS scale as a sensitive tool in detecting suicidal behaviours and measuring the severity of suicidality risks, offering a capability for broad reach and immediate assessment during clinical conversation between doctor and patient. Moreover, the RASS on-line psychometric instrument, when being freely distributed among the general population over internet sources, enabled to attract vulnerable groups of respondents with significantly higher suicidality risks. Future research should focus on integrating such tools into comprehensive suicide prevention programs and developing appropriate follow-up monitoring strategies for high risk-cases.

Virtual Reality (VR) Device with Integrated Biofeedback Sensors (ReViSide) to Cope with Emotional Burnout State Among Employees Experiencing Stress at Workplace: Problem Overview and Action Plan.

INTRODUCTION: In this study we examine the issue of employee burnout, caused by long-term exposure to workplace stressors, considering its complex phenomenology in the context of contemporary psychological and psychiatric views. Towards the development of innovative technologies to correct burnout in the context of psychosocial rehabilitation, we present our study protocol involving the ReViSide virtual reality (VR) and biofeedback intervention, including monitoring of respiratory rates and EEG rhythms. METHODS: The randomized controlled trial protocol includes adult participants aged 18 to 65 years (n=140) who exhibit emotional burnout in the workplace. The intervention group will undergo a course of VR correction (ReViSide), while the control group receives a standard psychocorrection. The primary endpoint will be level of emotional burnout to the Maslach Burnout Inventory (MBI). We shall also assess anxiety, depression, asthenia and subjective improvement in condition using validated scales (HADS, HARS, HDRS, VAS-A, PGI-C). RESULTS: We shall test our hypothesis that the VR-correction group will show significant improvements in MBI scores, particularly in emotional exhaustion, depersonalization, and personal accomplishment, compared to the control group. Secondary outcome measures are likewise expected to demonstrate more prominent improvements in the VR group, correlating with the magnitude of burnout reduction to MBI. Analysis of EEG data may reveal changes in alpha rhythm patterns during VR sessions, potentially correlating with reduced distress levels. CONCLUSIONS: We designed this study to test the integration of an interdisciplinary approach for treating burnout, highlighting the ReViSide technology. Confirming the efficacy of this approach for psychosocial rehabilitation targeting burnout states among employees should improve their stress resilience, daily motivation, and work productivity in the context of the modern high working pressure environment and demanding corporate culture.

Virtual Reality / Augmented Reality (VR/AR) Approach to Develop Social and Communication Skills in Children and Adolescents with Autism Spectrum Disorders Without Intellectual Impairment.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects a significant proportion of the world's population, particularly children and adolescents. The sensory processing issues can be an evidence-based target for therapeutic/corrective interventions by controlling the intensity and targeted replacement of maladaptive sensory stimuli with neutral stimuli using virtual reality or augmented reality. SUBJECTS AND METHODS: We searched for articles on Pubmed. The search query included ((VR or virtual reality) or (AR or augmented reality)) and (children or adolescents) and (ASD or autism spectrum disorder or autism). RESULTS: Our criteria were met by 25 articles. 19 articles used VR, 5 articles used AR and 1 article used MR. Most interventions offer children and adolescents with ASD individualized tasks. Immersive VR games developed collaborative skills. Other systems encourage and teach directed facial gaze. Evaluation of the effectiveness of learning in VR/AR environment is carried out by means of different scales, qualitative analysis of surveys, questionnaires and interviews, studying the number and duration of eye contacts between the participant and the avatar. It should be noted that almost all studies were conducted on small samples, so their results allow us to draw only preliminary conclusions about the effectiveness of VR /AR. CONCLUSIONS: The following key areas of VR/AR technologies for children and adolescents with high-functioning ASD can be identified: communicating with an avatar, including answering its questions, tracking the child's gaze and encouraging the child to look at the face, placing it in social situations close to real life, practicing common everyday situations, learning to recognize emotions. A VR/AR-based therapy approach may help children with autism spectrum disorder without cognitive impairment to develop higher levels of adaptation in terms of social and communication skills. However, more research is needed to evaluate the effectiveness of different methods.

Comparing the Anti-Depressive Effect of Electroconvulsive Therapy (ECT) Versus Transcranial Magnetic Stimulation (TMS) in the Treatment of Patients with Depression.

BACKGROUND: Electroconvulsive therapy (ECT) is one of the most effective treatments for depressive disorders. However, ECT has a number of limitations, such as significant side effects in the neurocognitive domain and the requirement for general anesthesia. Transcranial magnetic stimulation (TMS) is an intervention that applies electric stimulation to the brain without causing convulsions, thus representing an attractive alternative to ECT. The aim of our study is to review systematic reports of the effectiveness of ECT and TMS in the treatment of depressive spectrum disorders. SUBJECTS AND METHODS: We performed search queries in PubMed and eLibrary databases, which retrieved 391 articles, of which 14 met our inclusion criteria for the analysis. The articles comprised three comparisons: TMS vs SHAM, ECT vs sham ECT (SECT), and ECT vs PHARM. The protocol parameters analyzed for TMS were coil type, targeted brain area, amplitude of resting motor threshold, duration of session, number of sessions in total and per week, number and pulses per session and inter-train pause. For ECT, we evaluated the type of ECT device, targeted brain area, type of stimuli, and for ECT vs PHARM we recorded types of anesthesia and antidepressant medication. RESULTS: Three of 6 studies showed a therapeutic effect of TMS compared to placebo; efficacy was greater for TMS frequency exceeding 10 Hz, and with stimulation of two areas of cerebral cortex rather than a single area. There was insufficient data to identify a relationship between the success of TMS and intertrain pause (IP). Three of four studies showed a therapeutic effect of ECT compared to placebo. Three studies of bilateral ECT showed a significant reduction in depression scores compared to the SECT groups. ECT protocols with brief pulses were generally of lesser efficacy. Four of 5 ECT vs PHARM studies showed superior efficacy of ECT compared to PHARM. Among several antidepressants, only the ketamine study showed greater efficacy compared to ECT. CONCLUSIONS: There of six TMS studies and 7 of 9 ECT studies showed efficacy in reducing depressive symptoms. A prospective study of crossover design might reveal the relative efficacies of ECT and TMS.

Chronobiological Predictors of Depression Relapse: for Prognostic Model Development - a Systematic Review.

BACKGROUND: Depressive disorders are characterized by fluctuating symptom severity, and developing an individual prognostic model for relapse is crucial for effective prevention. Chronobiological factors are poorly understood in this context. METHODS: A systematic search was conducted to identify articles related to the prognosis of depression recurrence based on chronobiological factors. Relevant clinical studies were included, while reviews and case reports were excluded. A total of 14 articles were selected for review. RESULTS: The included articles focused on various chronobiological factors, including circadian biorhythms, individual chronotype, mood swings, seasonal patterns, diurnal cortisol fluctuations, and light therapy. The accuracy of personified prognosis ranged from 22.7% to 93.8%, and the prognostic value of specific predictors in group prognosis varied from 23.9% to 54%. Methodological differences and limitations hindered direct comparison and clinical applicability. CONCLUSIONS: Developing precise and practical models for depression recurrence prognosis remains limited. Parameters of circadian rhythm showed the highest accuracy for short-term prognosis, and the use of digital technologies, including AI, enhanced prognostic value. Relapse seasonality had limited practical applicability. Integrating other chronobiological factors into prognostic models requires further research. Utilizing digital technologies, including AI, can improve the accuracy and range of personified prognosis. Only a few selected parameters of the human chronobiological system were considered in the examined studies. There are indications of the other chronobiological factors that could be included in the integrated prognostic model of recurrence for its further improvement.

Neuronetwork Approach in the Early Diagnosis of Depression.

BACKGROUND: Depression is a common mental illness, with around 280 million people suffering from depression worldwide. At present, the main way to quantify the severity of depression is through psychometric scales, which entail subjectivity on the part of both patient and clinician. In the last few years, deep (machine) learning is emerging as a more objective approach for measuring depression severity. We now investigate how neural networks might serve for the early diagnosis of depression. SUBJECTS AND METHODS: We searched Medline (Pubmed) for articles published up to June 1, 2023. The search term included Depression AND Diagnostics AND Artificial Intelligence. We did not search for depression studies of machine learning other than neural networks, and selected only those papers attesting to diagnosis or screening for depression. RESULTS: Fifty-four papers met our criteria, among which 14 using facial expression recordings, 14 using EEG, 5 using fMRI, and 5 using audio speech recording analysis, whereas 6 used multimodality approach, two were the text analysis studies, and 8 used other methods. CONCLUSIONS: Research methodologies include both audio and video recordings of clinical interviews, task performance, including their subsequent conversion into text, and resting state studies (EEG, MRI, fMRI). Convolutional neural networks (CNN), including 3D-CNN and 2D-CNN, can obtain diagnostic data from the videos of the facial area. Deep learning in relation to EEG signals is the most commonly used CNN. fMRI approaches use graph convolutional networks and 3D-CNN with voxel connectivity, whereas the text analyses use CNNs, including LSTM (long/short-term memory). Audio recordings are analyzed by a hybrid CNN and support vector machine model. Neural networks are used to analyze biomaterials, gait, polysomnography, ECG, data from wrist wearable devices, and present illness history records. Multimodality studies analyze the fusion of audio features with visual and textual features using LSTM and CNN architectures, a temporal convolutional network, or a recurrent neural network. The accuracy of different hybrid and multimodality models is 78-99%, relative to the standard clinical diagnoses.

G.T. MSRS On-Line Calculator Targeting the Early Diagnosis of Mixed Affective States: the Multicenter Study Project Design on the Approbation and Validity of the Three Language Versions of the Rating Scale.

BACKGROUND: Mixed affective states (MS) are often misdiagnosed by the clinicians and lead to the inappropriate treatment strategies contributing to the severe forms, poor outcome with higher rates of comorbid conditions and worse remission quality in affective and bipolar disorders, as well as to a decreased psychosocial functioning of these patients. The development of reliable tools for the MS assessments or so called the phenomenon of mixity in affective disorders, is still an unmet need of psychiatric research and clinical practice. In this paper, we present PC program "Multilingual IBM-PC on-line calculator for early diagnosis of the mixed affective states" based on the Giuseppe Tavormina Mixed States Rating Scale (G.T. MSRS) (Russian, English, Italian language versions) created by the ICERN group using programming language JavaScript, working for such operation systems (OS) as Windows, Linux, MacOs, Android, iOS, and aims to contribute to the accurate assessment of the presence and severity of the mixed states among affective disorders. SUBJECTS AND METHODS: The G.T. Mixed States Rating Scale on-line calculator consists of 11 items which evaluate various aspects of MS in patients with major depression, bipolar or recurrent depressive disorder. A total score is automatically calculated, considering the type of affective temperament according to the Akiskal's and Tavormina's schemas, thus, the specific sub-groups of MS are differentiated based on the ranges: Medium-light (2-6), Medium (7-12), and High (13-19) Mixity level. The study will enroll 330 participants during two (three months follow-up) visits (110 native speakers in each of the three languages) of both genders aged from 18 till 55 y.o. with the diagnoses of depressive episodes, major depression, bipolar or recurrent depressive disorder according to the DSM-5 criteria. Assessments will be provided by the two investigators (second one will be blinded to the G.T. MSRS results obtained by the first researcher), based on the use of DSM-5 clinical interview, Young Mania Rating Scale, Montgomery-Åsberg Depression Rating Scale, Clinical Global Impression - Severity scale (CGI-S), Clinical Global Impression - Improvement scale (CGI-I), Patient Global Impression of Change (PGIC). RESULTS: The study will assess the agreement between the diagnostic category/clinical impression and the on-line G.T. MSRS calculator use results, its test-retest reliability, and diagnosis stability for further assessment of the on-line G.T. MSRS calculator validity and clinical utility. Secondary variables will evaluate internal reliability and such statistical analyses as Cronbach's alpha, Cohen's Kappa, biserial correction, and agreement between initial and follow-up diagnoses. CONCLUSIONS: Current multicenter validation study of the on-line G.T. MSRS calculator will enhance the understanding of the mixity phenomenon and its clinical implication, aiming to improve the treatment strategies to manage the course of mental disorder, quality of life and psychosocial functioning in patients with affective (bipolar) disorders, accompanied by MS, and a clinical recommendation for the routine administration of the user-friendly on-line G.T. MSRS version in clinical practice.

Peripheral Blood Mononuclear Cell-Related Biomarkers in Schizophrenia.

INTRODUCTION: Schizophrenia is a severe mental illness causing significant impairment in personal, family, social, educational, occupational, and other important areas of life. While there is no widely accepted endophenotype, peripheral blood cells may serve as an accessible model of intracellular changes in schizophrenia. METHODS: We reviewed the literature on the query "peripheral blood mononuclear cells AND schizophrenia" in Medline (Pubmed), selecting studies that searched for specific biomarkers of schizophrenia. We considered both diagnostic biomarkers and biomarkers of therapeutic response, specific schizophrenia disorders or differential diagnostic biomarkers. RESULTS: We retrieved 41 articles matching the search criteria, among which were studies that considered changes in the production of pro-inflammatory and anti-inflammatory markers, proteins, receptors, enzyme activity, and gene expression as potential biomarkers. CONCLUSION: Approaches analysing a biological axis or a group of related biomarkers may hold the greatest promise for identifying schizophrenia. In addition, pharmacological status, smoking status, inflammatory markers and glucose metabolites, the presence of comorbidities should be considered. Certain biomarkers, while not specific for the diagnosis of schizophrenia, may indicate the prognosis and effectiveness of treatment in the established diagnosis.

Pharmacogenetic Aspects of COVID-19 Management and Post-COVID-19 Depression Treatment with Fluvoxamine.

BACKGROUND: Quarantine measures with self-isolation of varying duration have been significant psychosocial stressors in the context of the COVID-19 pandemic. The serotonin selective reuptake inhibitor fluvoxamine has been considered as a prophylaxis against depression in early COVID-19 patients, with additional benefits apparently arising from its antiviral activity. In this narrative review, we draw attention to the body of evidence showing efficacy of fluvoxamine in protecting against depressive disorders in COVID-19 patients, while also attenuating the severity of COVID-19 disease, with a notable reduction in the need for intubation and lower mortality. We consider this potential two-fold action of fluvoxamine in the light of its pharmacogenetic and pharmacological profiles. SUBJECTS AND METHODS: Full-text publications in English and Russian in Google Scholar, PubMed, NCBI, Web of Science, and E-Library databases were selected by keywords, solitary and in combination (fluvoxamine, COVID-19, depression, anxiety, antidepressants, adverse reactions) for the period from March 01, 2020 to June 06, 2022. We also analyzed the full-text publications in English and Russian language reporting adverse reactions caused by fluvoxamine use for the period from 2012 to 2022. RESULTS: The literature search yielded 10 papers reporting on the efficacy fluvoxamine in relieving depressive symptoms in COVID-19 patients, and 3 papers on its effect on medical outcome. The preponderance of data indicated a dual therapeutic action of fluvoxamine, and our further literature investigation was informative about drug-drug interactions and genetic factors moderating the antidepressant efficacy of fluvoxamine. CONCLUSIONS: Patients with COVID-19 seeking psychopharmacological treatment for depressive symptoms must be informed of the benefits and risks of fluvoxamine use. Several lines of findings indicate this agent to possess an additional antiviral action. However, optimal dosage regimens and the trade-off with drug-drug interactions remain unclear. Pharmacogenetic testing may assist in evidence-based optimization of fluvoxamine dosages in the context of COVID-19 infection with comorbid depression.

The Efficacy of Mobile Phone-Based Interventions for the Treatment of Depression: A Systematic Meta-Review of Meta-Analyses of Randomized Controlled Trials.

BACKGROUND: Depression is ranked by the World Health Organization as the single largest contributor to global disability. The shortage of health care resources, conditions of social distancing during the present pandemic, and the continuing need of patients with subclinical depression and in remission for supportive therapies, all together motivate a search for new approaches to deliver appropriate and timeous treatment for depression. SUBJECTS AND METHODS: We conducted a systematic literature search of meta-analyses and systematic reviews on the topic of mobile apps for the treatment of depression using the Medline (Pubmed) database during the period ending March 30th, 2022. This review was managed following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and entailed a search strategy using key-words related to depressive states and mobile phone apps for depression treatment and management. RESULTS: A total of 15 full-text articles met the inclusion criteria for the current systematic review. 13 of the 15 studies reported on the effectiveness of mobile apps for treating depression, finding a significant reduction in depressive symptoms with small-to-medium positive effect size. Patients with severe depression experienced greater benefits from a behavioral activation app, whereas those with mild depression responded better to a mindfulness app. The impact of clinicians' support is difficult to isolated completely from the particular interventions' effects. CONCLUSIONS: Mobile-based intervention apps present a convenient tool for prevention and supportive therapy of depression. The use of mobile apps may act as an efficient intervention to reduce depression in adult patients regardless the potential contributing factors of gender or co-morbidities, but the role of mobile apps should be contrasted with other digital interventions.